{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d768c9b1-c5a7-417a-9fac-5fcbd6944fe6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from dotenv import load_dotenv\n",
    "from openai import OpenAI\n",
    "import anthropic\n",
    "from IPython.display import Markdown, display, update_display\n",
    "import ollama"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "80a4e740-75d0-4272-b02e-0b77b0a143ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "system_message = \"You are an assistant that is great at telling jokes\"\n",
    "user_prompt = \"Tell a light-hearted joke for an audience of Data Scientists\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f2ef28e5-5073-4065-b066-387181df063a",
   "metadata": {},
   "outputs": [],
   "source": [
    "prompts = [\n",
    "    {\"role\": \"system\", \"content\": system_message},\n",
    "    {\"role\": \"user\", \"content\": user_prompt}\n",
    "  ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d54e910a-cdbf-49cb-9924-265d9845d622",
   "metadata": {},
   "outputs": [],
   "source": [
    "#direct display wihtout streaming\n",
    "response = ollama.chat(\n",
    "                model=\"llama3.2\",\n",
    "                messages=prompts,\n",
    "                options={\n",
    "                    \"temperature\": 0.7\n",
    "                }\n",
    "                \n",
    "            )\n",
    "result = response['message']['content']\n",
    "display(Markdown(result))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "47dd7965-fdfc-4472-b2f6-c98f755964f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "#This is with streaming \n",
    "stream = ollama.chat(\n",
    "                model=\"llama3.2\",\n",
    "                messages=prompts,\n",
    "                stream=True\n",
    "            )\n",
    "response = \"\"\n",
    "display_handle = display(Markdown(\"\"), display_id=True)\n",
    "for chunk in stream:\n",
    "    content = chunk.get('message', {}).get('content', '')\n",
    "    if content:\n",
    "        response += content.replace(\"```\", \"\")\n",
    "        update_display(Markdown(response), display_id=display_handle.display_id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ef13e3ae-bde7-4e3a-9fcd-0a9bfd1caef0",
   "metadata": {},
   "outputs": [],
   "source": [
    "#direct display wihtout streaming, using deepseek-r1\n",
    "response = ollama.chat(\n",
    "                model=\"deepseek-r1\",\n",
    "                messages=prompts\n",
    "                \n",
    "            )\n",
    "result = response['message']['content']\n",
    "display(Markdown(result))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ddc4fe91-3d5b-4d45-83bf-f349597c672c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#direct display wihtout streaming, using qwen3\n",
    "response = ollama.chat(\n",
    "                model=\"qwen3\",\n",
    "                messages=prompts\n",
    "                \n",
    "            )\n",
    "result = response['message']['content']\n",
    "display(Markdown(result))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2beb6731-41e3-42a4-a8d3-5f0ef644f2f3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.12"
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 "nbformat": 4,
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